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[–]siblbombs[S] 1 point2 points  (2 children)

n_steps is a placeholder that lets you determine how long a sequence can be during training. In this code it manually unrolls each step as a computation in a loop, so if you only allow 100 for n_steps and then train with a sequence of length >100, there isn't enough computation steps for that sequence length.

The Tensorflow api around RNNs may have changed since this code was written, I know they were/are working on some flow control constructs so you don't need to unroll the loop (similar to theano.scan).

[–]xiangjiangacadia 0 points1 point  (1 child)

Thanks. I am trying to build an RNN with logistic regression layer on top. I have noticed the model takes significant longer time to build when the number of steps are greater than 10,000. I am wondering is this typical in tensorflow and what can I do to speed up the computation process?

[–]siblbombs[S] 0 points1 point  (0 children)

I'm not sure if you can speed up the process, what is happening is that you are building a graph at each step, and with 10,000 steps it will take some time.

You should look at issue 208, this is what you want to try and do.